Methods Of Mathematical Finance
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Mathematical Methods for Financial Markets
Author: Monique Jeanblanc
language: en
Publisher: Springer Science & Business Media
Release Date: 2009-10-03
Mathematical finance has grown into a huge area of research which requires a large number of sophisticated mathematical tools. This book simultaneously introduces the financial methodology and the relevant mathematical tools in a style that is mathematically rigorous and yet accessible to practitioners and mathematicians alike. It interlaces financial concepts such as arbitrage opportunities, admissible strategies, contingent claims, option pricing and default risk with the mathematical theory of Brownian motion, diffusion processes, and Lévy processes. The first half of the book is devoted to continuous path processes whereas the second half deals with discontinuous processes. The extensive bibliography comprises a wealth of important references and the author index enables readers quickly to locate where the reference is cited within the book, making this volume an invaluable tool both for students and for those at the forefront of research and practice.
Financial Statistics and Mathematical Finance
Mathematical finance has grown into a huge area of research which requires a lot of care and a large number of sophisticated mathematical tools. Mathematically rigorous and yet accessible to advanced level practitioners and mathematicians alike, it considers various aspects of the application of statistical methods in finance and illustrates some of the many ways that statistical tools are used in financial applications. Financial Statistics and Mathematical Finance: Provides an introduction to the basics of financial statistics and mathematical finance. Explains the use and importance of statistical methods in econometrics and financial engineering. Illustrates the importance of derivatives and calculus to aid understanding in methods and results. Looks at advanced topics such as martingale theory, stochastic processes and stochastic integration. Features examples throughout to illustrate applications in mathematical and statistical finance. Is supported by an accompanying website featuring R code and data sets. Financial Statistics and Mathematical Finance introduces the financial methodology and the relevant mathematical tools in a style that is both mathematically rigorous and yet accessible to advanced level practitioners and mathematicians alike, both graduate students and researchers in statistics, finance, econometrics and business administration will benefit from this book.
Advanced Mathematical Methods for Finance
"The title of this volume 'Advanced Mathematical Methods for Finance, ' AMaMeF for short, originates from the European network of the European Science Foundation with the same name that started its activity in 2005. The goals of its program have been the development and the use of advanced mathematical tools for finance, from theory to practice. This book was born in the same spirit of the program. It presents innovations in the mathematical methods in various research areas representing the broad spectrum of AMaMeF itself. It covers the mathematical foundations of financial analysis, numerical methods, and the modeling of risk. The topics selected include measures of risk, credit contagion, insider trading, information in finance, stochastic control and its applications to portfolio choices and liquidation, models of liquidity, pricing, and hedging. The models presented are based on the use of Brownian motion, Lévy processes and jump diffusions. Moreover, fractional Brownian motion and ambit processes are also introduced at various levels. The chosen blending of topics gives a large view of the up-to-date frontiers of the mathematics for finance. This volume represents the joint work of European experts in the various fields and linked to the program AMaMeF."--Preface.